We are looking for a skilled and motivated Databricks Developer with strong expertise in SQL, Python, Apache Spark, and cloud-based data engineering solutions. The ideal candidate will be responsible for building scalable data pipelines, enabling analytics and reporting solutions, and supporting AI/ML workloads using the Databricks platform. Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark. Develop ETL/ELT workflows for processing large-scale structured and unstructured datasets. Write optimized SQL queries and Python-based data transformation scripts. Build and manage data ingestion frameworks from multiple data sources. Implement batch and real-time data processing solutions. Collaborate with analytics, reporting, and business teams to deliver data-driven insights. Support AI/ML workloads by preparing and transforming datasets for model training and inference. Optimize Spark jobs for performance, scalability, and cost efficiency. Develop reusable notebooks, workflows, and orchestration pipelines. Ensure data quality, governance, security, and compliance standards are maintained. Troubleshoot production issues and provide performance tuning recommendations. Work closely with cross-functional teams including Data Engineers, Data Scientists, Analysts, and Cloud Architects. Required Skills Strong experience with SQL and Python programming. Hands-on experience with Apache Spark and PySpark. Expertise in Databricks platform and notebook development. Experience in building data pipelines and ETL workflows. Good understanding of Data Lake, Delta Lake, and Lakehouse architecture. Experience with analytics and reporting solutions. Knowledge of AI/ML data preparation and workload integration. Familiarity with workflow orchestration tools and CI/CD practices. Strong understanding of data modeling and performance optimization techniques. Experience working with cloud platforms such as Azure, AWS, or GCP. Preferred Skills Experience with Azure Data Factory (ADF), Synapse, or similar services. Knowledge of streaming technologies like Kafka or Spark Streaming. Familiarity with Power BI, Tableau, or other reporting tools. Exposure to MLflow, model deployment, or MLOps concepts. Understanding of DevOps and Infrastructure as Code (IaC). Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or related field. Relevant certifications in Databricks, Spark, or Cloud technologies are a plus. Key Competencies Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to work in agile and fast-paced environments. Strong attention to detail and data accuracy. Nice to Have Experience with Generative AI or AI-driven analytics solutions. Exposure to modern data architecture and cloud-native technologies. Experience in enterprise-scale data migration projects. Skills: python,apache spark,databricks,gen ai